Note that the input of the 3D PatchGAN classifier \(D\)  was also conditioned on \(x\) , as it was found critical for GAN to produce realistic outputs [1]}. A L1 reconstruction loss \(L_{L1}\)  which encouraged less blurring [1]} was used and expressed as
\(L_{L1}(G)=\mathbb {E}_{x,y}[||y-G(x)||_{1}]\) 
